Dr. Andrius Kučas (p), Dr. Matteo Berzi, Dr. Benedikt Herrmann

This study presents a gravity-based methodological framework for estimating cross-border connectivity and potential commuter flows between regional labour markets. The proposed Gravity-Based Commuter Proxy Model provides a policy-relevant analytical approach for analysing functional labour interactions in situations where observed commuting statistics are incomplete or unavailable. The method supports evidence-based regional analysis by translating socioeconomic indicators into spatial interaction patterns that approximate labour mobility dynamics. The framework conceptualises commuting as a response to structural imbalances between labour supply and employment opportunities across regions. Areas characterised by surplus working-age population generate outward commuting pressure, while regions offering stronger labour demand and higher economic attractiveness act as employment destinations. These relationships are operationalised through a spatial interaction model in which the intensity of commuting increases with economic opportunity and decreases with spatial separation. The methodological workflow combines a conceptual labour-market model, a gravity-based interaction formulation, and a geospatial implementation environment. Labour surplus in origin regions and employment capacity in destination regions form the primary drivers of interaction, while wage conditions represent economic attractiveness and geographic distance introduces spatial friction. Estimated commuting flows are distributed proportionally among alternative destinations and subsequently balanced to maintain consistency between labour supply and demand constraints. Model outputs include regional indicators describing commuter departures, arrivals, and populations without accessible employment opportunities, alongside directional flow networks representing predicted commuting linkages. The methodology is implemented using harmonised regional socioeconomic data and automated spatial processing procedures, producing spatially coherent commuting structures aligned with established principles of regional economics. Metropolitan regions emerge as primary labour attractors, suburban areas demonstrate balanced exchange dynamics, and rural regions predominantly function as labour-exporting territories. Cross-border commuting patterns concentrate along economically integrated neighbouring regions, reflecting wage differentials, proximity, and labour market complementarities. The results demonstrate that cross-border commuting represents a structural component of regional labour market integration rather than a marginal phenomenon. The proposed framework offers a transparent, scalable, and transferable tool for analysing labour mobility in data-scarce environments and supports policymaking in regional development, transport planning, and cross-border cooperation by providing an interpretable representation of functional economic connectivity across territorial scales.

Dr. Olle Järv (p)

One of the main objectives of the EU is to enhance integration and cohesion within internal border regions by strengthening political, economic, and social ties through cross-border cooperation and governance. While institutional and economic ties across borders are well examined and understood, people’s perspectives are less well known. Beyond potential access to cross borders, people’s actual interactions and cross-border practices are challenging to capture. Yet these social interactions contribute to the (re)production of functional cross-border regions. Besides cross-border commuting, one significant yet overlooked interaction relates to routine cross-border shopping and the use of services. To provide new insights into how shopping and service use create functional cross-border regions, we use human mobility as a tool to capture this phenomenon.
Here, we use a mobile big data source to reveal people’s cross-border mobility behaviour and examine movements across state borders linked to shops and shopping centres in Europe. By separating flows from both sides of a border, we show how the proportion and directionality, temporal rhythms, and spatial extent of cross-border mobility flows enable us to characterize functional border regions from the perspective of shopping and service use. We compare workdays and weekends, and statistically examine which regional characteristics are associated with functional cross-border regions from the perspective of shopping and service use. Our initial findings suggest different types of cross-border shopping behaviour, both in temporal rhythms and spatial patterns. We conclude by addressing how shopping and the use of services across state borders contribute to functional cross-border regions as one important layer, and we discuss ways of using mobile big data to support policy and planning in border regions in the European Union and beyond.

Ms Claire Duvernet (p), Dr Philipp Gareis

Functional Urban Areas (FUAs) are widely used in urban and regional analysis to capture the functional reality of cities beyond administrative borders. The EU–OECD methodology defines FUAs based on urban centres and commuting zones, but this approach relies heavily on commuting data and national administrative units. In cross-border regions, such delineations often fail to reflect everyday realities, as residents may cross national borders not only for work but also for shopping, leisure, or healthcare. Traditional commuter-based classifications therefore capture only one dimension of cross-border interaction.
Recent research has attempted to integrate a cross-border dimension into FUA delineation, using indicators such as population distribution, accessibility of border crossings, or mobile big data flows. However, these approaches face challenges related to data availability, comparability, and reproducibility. In response, this paper proposes a complementary accessibility-based perspective that focuses on the potential to reach services across borders within defined travel time thresholds.
We develop a multi-service accessibility framework using a rapid realistic rooting tool that analyses access to healthcare facilities, leisure and cultural amenities, and major shopping agglomerations. Using a rapid realistic routing tool, accessibility is calculated for different transport modes and differentiated by demographic groups to identify potential age-related disadvantages. By disaggregating service categories and population groups, we reveal overlapping and diverging spatial patterns of cross-border functional integration.
The French–German border region serves as a case study. Building on existing classifications and previous analyses, we compare accessibility-based functional areas with national spatial categories and stakeholder perceptions collected during previous workshops in the Eurodistricts Saar-Moselle and Oberrhein. Preliminary results show multiple potential cross-border functional areas depending on service type and modal split. By overlaying objective accessibility measures with subjective perceptions, the study highlights convergences and mismatches between data-driven delineations and lived spatial realities.
The paper argues that integrating multi-service accessibility into FUA delineation enriches existing methodologies and supports more nuanced cross-border planning and governance.